Lean Layer Logo

Lean Layer

RevOps Analytics Engineer

Reposted 25 Days Ago
Remote
Hiring Remotely in United States
40K-120K Annually
Mid level
Remote
Hiring Remotely in United States
40K-120K Annually
Mid level
The RevOps Analytics Engineer is responsible for maintaining data infrastructure, building reliable data systems, and supporting revenue analytics through effective data modeling and ETL/ELT processes.
The summary above was generated by AI
Position Overview

Lean Layer is the #1 Rated RevOps Agency on G2, and we’re doubling our consulting team over the next year. Our reputation is built on excellent results, which means we need to keep hiring excellent people. We are looking for a RevOps Analytics Engineer with deep Revenue Operations expertise to own and maintain the data infrastructure that powers revenue analytics and reporting across our client environments.

This role focuses on data engineering and warehouse management, ensuring reliable pipelines, scalable data models, and high-quality revenue data. The RevOps Analytics Engineer will work closely with RevOps consultants who define CRM and business requirements, and with data analysts who build dashboards and reporting.

You may be a fit for the RevOps Analytics Engineer role if you are strong in SQL, data modeling, and warehouse architecture, and can understand the business context of revenue operations in order to build reliable and scalable data systems.


What We’re Looking For

The ideal candidate:

  • Enjoys building reliable data systems and solving complex data problems

  • Has strong technical data engineering skills

  • Understands how revenue teams use data for reporting and decision-making

  • Can translate business context into scalable data models

  • Is comfortable working across multiple systems and client environments

  • Is comfortable working directly with clients as needed

  • Thrives in collaborative, fast-paced environments


Key Responsibilities

Data Warehouse Ownership:

  • Design and maintain datasets and table structures

  • Manage warehouse performance, partitioning, clustering, and cost optimization

  • Maintain access controls and permissions

  • Structure warehouse schemas to support revenue analytics and reporting

Data Pipelines & Integrations:

  • Build and maintain ETL / ELT pipelines from revenue systems into the warehouse

  • Integrate data from systems such as HubSpot, Salesforce, marketing and sales analytics platforms, sales engagement platforms, billing systems, and product analytics tools

  • Monitor pipeline health and resolve failures

  • Manage schema changes from upstream systems

  • Ensure reliable and timely data synchronization

  • Manage GitHub repositories

Data Modeling for Revenue Analytics:

  • Design and maintain analytics-ready data models

  • Build models for accounts, contacts, opportunities, and pipeline data

BI & Analytics Support:

  • Maintain tables and models used by BI tools such as Looker

  • Optimize queries and support derived tables used in reporting

  • Ensure consistent metric definitions across reporting layers

  • Dashboard creation for data validation

Data Quality & Reliability:

  • Implement data validation and testing

  • Monitor pipeline health and data freshness

  • Identify and resolve data inconsistencies

  • Maintain documentation for warehouse models and data definitions


Required Qualifications
  • 3–5 years of experience in data engineering or analytics engineering

  • Strong SQL skills

  • Experience working with data warehouses (BigQuery, Snowflake, Redshift, etc.)

  • Experience working with Salesforce or HubSpot as a data source

  • Experience building and maintaining ETL / ELT pipelines

  • Experience designing analytics-ready data models

  • Familiarity with API-based integrations and data syncing

  • Python for data pipelines or automation

  • Reverse ETL or operational data workflows

  • dbt or similar transformation tools

  • Looker or similar BI platforms

  • Experience with GitHub


Preferred Experience

Experience working with revenue or business systems and terminology such as:

  • Marketing Automation Platforms (MAP) like HubSpot

  • Marketing analytics platforms

  • SaaS revenue metrics (ARR, ACV, TCV, MRR, etc.)

  • SaaS terminology (MQL, SQL, SQO, Deal/Opportunity, Lead/Contact, etc.)


Learn more about what it's like to work at Lean Layer here.
Visa Sponsorship: Please note that we are not currently able to offer U.S. visa sponsorship or transfer for this position.
For Canadian and Brazilian Residents: We also invite you to apply for this position but please note that at this time we can only hire those outside of the United States as full-time contractors. If you have any questions about this set up, please don't hesitate to reach out.

Similar Jobs

5 Hours Ago
Remote or Hybrid
Mid level
Mid level
Big Data • Marketing Tech • Sales • Software • Analytics • Big Data Analytics
The Manual QA Engineer at PureSpectrum will focus on API testing, ensure product reliability, validate data in MongoDB, and collaborate across teams to enhance quality.
Top Skills: ConfluenceJIRAMongoDBPostman
2 Days Ago
Remote or Hybrid
Junior
Junior
Cloud • Computer Vision • Information Technology • Sales • Security • Cybersecurity
The role focuses on expanding MSSP partner relationships in Brazil, driving revenue growth through upsell and account management, and collaborating with internal teams.
Top Skills: Salesforce
2 Days Ago
Remote or Hybrid
Mid level
Mid level
Cloud • Computer Vision • Information Technology • Sales • Security • Cybersecurity
The Regional Marketing Manager will create and execute marketing plans, partner with sales, manage projects, and analyze marketing metrics to support business goals in the Brazil region and other LatAm Spanish countries.
Top Skills: Digital MarketingMarketingSalesforce

What you need to know about the Seattle Tech Scene

Home to tech titans like Microsoft and Amazon, Seattle punches far above its weight in innovation. But its surrounding mountains, sprinkled with world-famous hiking trails and climbing routes, make the city a destination for outdoorsy types as well. Established as a logging town before shifting to shipbuilding and logistics, the Emerald City is now known for its contributions to aerospace, software, biotech and cloud computing. And its status as a thriving tech ecosystem is attracting out-of-town companies looking to establish new tech and engineering hubs.

Key Facts About Seattle Tech

  • Number of Tech Workers: 287,000; 13% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Amazon, Microsoft, Meta, Google
  • Key Industries: Artificial intelligence, cloud computing, software, biotechnology, game development
  • Funding Landscape: $3.1 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Madrona, Fuse, Tola, Maveron
  • Research Centers and Universities: University of Washington, Seattle University, Seattle Pacific University, Allen Institute for Brain Science, Bill & Melinda Gates Foundation, Seattle Children’s Research Institute

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account